A. Kabeer
Papers
1
Total Citations
2
H-Index
1
About
A. Kabeer is a researcher at the forefront of assistive neurotechnology, specializing in brain-computer interfaces (BCIs) for mobility assistance. Their work focuses on developing and comparing EEG-based classification models that enable brain-controlled wheelchairs, offering transformative solutions for individuals with severe motor impairments. Kabeer’s most-cited paper, “Brain–Computer Interfaces for Mobility Assistance: A Comparative Analysis of EEG-Based Classification Models for Brain-Controlled Wheelchairs” (2024), has garnered 2 citations, reflecting early interest in their systematic evaluation of machine learning algorithms for decoding neural signals into real-time wheelchair commands. This contribution addresses critical challenges in BCI reliability and user adaptability, bridging gaps between signal processing, human-computer interaction, and rehabilitation engineering. Kabeer’s research holds promise for enhancing independence and quality of life, positioning them as an emerging voice in the integration of AI with assistive devices. Their work is particularly relevant for students and researchers exploring non-invasive neural interfaces, offering a practical framework for advancing accessible mobility technologies.
Research Focus
Key Achievements
Top Papers
- 1